I built a job recommender for people 0-3 years out of college in non-technical roles. This recommender uses NLP and ML to parse your resume and return which job archetype you fit best into.

Code to parse information such as Name, Email, Phone Number, Skill sets and Qualification from a given resume.

Artificial Intelligence has recently been used to automate resume parsing which deciphers various resumes using an NLP (Natural Language Processing) engine. It is important for recruiters as it may locate excellent candidates with a perfect match in qualifications, talents, and experience in a similar industry.

Resume Parser and Summariser using spaCy (NLP)

Automated Resume Screening application using NLP and ML to parse and evaluate resumes according to best fit to job description

Lightweight JavaFX NLP tool for resume parsing and job matching using TF-IDF, cosine similarity, and structured skills–experience–education extraction

The Smart Resume Analyzer is an AI-based tool designed to automate the resume screening process. It parses resumes, extracts key information (skills, experience, education), and compares them to job descriptions using Natural Language Processing (NLP). The system scores and ranks candidates based on job fit and provides feedback for improvement.

Resume-Score: Streamlit tool for automating resume parsing using NLP models to extract key data.

The project aims to create a Resume Parsing and Hiring Automation System using NLP and machine learning to automate the hiring process. It will parse resumes, extract details, match candidates with job descriptions, and rank profiles to select suitable candidates, ensuring efficiency, accuracy, and bias reduction.

ParsePro: A React and Node.js app that extracts keywords (skills, experience, education) from uploaded resumes (PDF/DOCX) using NLP, featuring a dark theme, progress bar, and keyword download, built with Material-UI, Axios, Multer, PDF-Parse, Mammoth, and Compromise.

AI-Driven Resume Screening System: An intelligent hiring platform that uses NLP and machine learning to automatically parse, rank, and match candidate resumes with job descriptions, featuring explainable AI rankings, bias detection, and an interactive chatbot for interview preparation.

This project uses Natural Language Processing (NLP) to automate resume parsing and rank candidates based on job relevance. It enables recruiters to efficiently shortlist the best candidates by extracting structured information from resumes and matching them against job descriptions.

SmartRecruit is an AI-driven recruitment platform that automates CV analysis, enhances candidate-job matching, and provides insightful analytics to optimize hiring decisions. Using NLP and machine learning, it supports advanced resume parsing, search, and filtering with Elasticsearch

Name entity recognition utilized for the Resume parser using NLP spacy tool in python

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Resume Parser built using python,pdfminer and NLP

A resume parser and skill matcher project using NLP and Machine Learning.

USES NLP TECHNIQUES TO PARSE AND READ RESUME'S

The Resume Parser NLP Project is an intelligent tool designed to extract and analyze key information from resumes using Natural Language Processing (NLP)

An NLP project for parsing the resume using spacy library and hugging face model

AI-powered resume analyzer that parses uploaded resumes, identifies skill gaps, and recommends personalized courses to boost job readiness using NLP.

NLP-powered resume screening app — parses PDFs, ranks candidates by JD match using TF-IDF + cosine similarity, detects skill gaps, scores resumes. Built with Python + Streamlit + Django.

AI-powered Resume & Job Description Semantic Matcher using NLP, BERT embeddings, cosine similarity scoring, and smart resume parsing. Includes dataset samples, notebooks, modular Python code, and documentation.

Automated Resume Parser is a web application that extracts key details from PDF resumes. It uses Flask, spaCy (NLP), and pdfplumber to identify name, email, skills, and education. The extracted data is stored in a PostgreSQL database for easy resume screening.

Built NLP-based system to parse, embed, and rank resumes using Sentence Transformers, Implemented cosine similarity ranking and skill extraction, Deployed using Streamlit, Integrated explainability module for HR transparency

🚀 AI Resume Screening & Ranking System | Streamlit + ML An AI-powered tool for resume parsing & ranking using TF-IDF & Cosine Similarity. ✅ PDF Resume Extraction | ✅ ML-Based Ranking | ✅ Streamlit Web App 🔗 Tech: Python | NLP | Machine Learning | Streamlit | Pandas | PyPDF2

NLP and RAG powered academic interview analysis for prospective job seekers. Enter your resume, job description, and simulate an interview at different levels of experience. Get graded with the Likert scale via the Amazon Mechanical Turk method, using Llama-LLM and NLP parsing.

Tools/Tech Stack: Python, Flask, Gemini AI API, HTML/CSS, JavaScript, Git, RESTful APIs, PythonAnywhere • ML/NLP Techniques: Resume parsing, keyword extraction, career clustering using embeddings • Problem Solved: Helped students and job seekers receive personalized career roadmaps and skill recommendations by analyzing their resumes & preferences

AI Job Recommendation System An AI-powered system that helps job seekers find relevant job opportunities by analyzing their resume, skills, and experience. The system uses NLP and machine learning to match candidates with suitable job postings and provides personalized recommendations. Features: Resume parsing and profile extraction Job search

Resume parser using NLP